The Stats Room: Week 4 QB Projections

The Stats Room: Week 4 QB Projections

This article is part of our The Stats Room series.

What a difference a week makes. Last week, nothing went right. This week, everything seems better, especially with the quarterbacks. Besides going over the results, I have gone down several wormholes this week and have made some decent discoveries.

First off, a little note on projections. They can vary greatly and owners should have an idea on the variation between projections and the results. For instance, here are the actual quarterback results (95 percent range) grouped by rounded projected results (a bit lower because of injured quarterbacks).

I'm not sure what the most important takeaway is from the data but several pieces are important. First, my projection's range of possible outcomes (at the 95 percent level) is +/- 15 points. A quarterback projected for 15 points is most like to produce somewhere between zero and 30 points. At that range, 100 percent guesswork may be an option for most owners. Hopefully, I can improve these results.

Second, after comparing my values to the standard RotoWire projections, the range of outputs for my values is within the industry norm. With most other projections likely having a similar outcome range, I can see why creators don't brag up their results. Their projections could be the best in the industry, but they're still not acceptably accurate.

Third, and most important, owners might not want to know the inherent risk of each player. They just want to go with their best team and not know their results mostly tied to inherent variation.

With the

What a difference a week makes. Last week, nothing went right. This week, everything seems better, especially with the quarterbacks. Besides going over the results, I have gone down several wormholes this week and have made some decent discoveries.

First off, a little note on projections. They can vary greatly and owners should have an idea on the variation between projections and the results. For instance, here are the actual quarterback results (95 percent range) grouped by rounded projected results (a bit lower because of injured quarterbacks).

I'm not sure what the most important takeaway is from the data but several pieces are important. First, my projection's range of possible outcomes (at the 95 percent level) is +/- 15 points. A quarterback projected for 15 points is most like to produce somewhere between zero and 30 points. At that range, 100 percent guesswork may be an option for most owners. Hopefully, I can improve these results.

Second, after comparing my values to the standard RotoWire projections, the range of outputs for my values is within the industry norm. With most other projections likely having a similar outcome range, I can see why creators don't brag up their results. Their projections could be the best in the industry, but they're still not acceptably accurate.

Third, and most important, owners might not want to know the inherent risk of each player. They just want to go with their best team and not know their results mostly tied to inherent variation.

With the range of results known, here are the results from last week.

PLAYERPASS ATTSPREADHYBRIDROTOWIREAVGDIFFACTUALHYBRID DIFFROTOWIRE DIFFAVG DIFF
Aaron Rodgers 20.3 18.7 20.3 20.1 14.6 0.2 24.8 4.5 4.7 10.2
Alex Smith 17.2 18.7 17.2 13.6 14.6 3.7 15.1 2.1 1.5 0.5
Andy Dalton 17.5 16.7 17.5 12.8 14.6 4.7 16.3 1.2 3.5 1.7
Ben Roethlisberger 16.5 16.1 16.5 14.8 14.6 1.8 12 4.5 2.8 2.6
Blake Bortles 17.5 15.1 17.5 10.7 14.6 6.7 27.6 10.1 16.9 13
Brian Hoyer 15 15.1 15 9.7 14.6 5.3 26.2 11.2 16.5 11.6
Cam Newton 18.5 19.2 18.5 16.9 14.6 1.6 8.3 10.2 8.6 6.3
Carson Palmer 17 15.5 17 12.4 14.6 4.6 17.7 0.7 5.3 3.1
Carson Wentz 16.4 15 16.4 14.5 14.6 1.9 13.2 3.2 1.3 1.4
Case Keenum 8.5
Dak Prescott 15.9 18.4 15.9 15.1 14.6 0.8 16.7 0.8 1.6 2.1
Derek Carr 16.8 17.4 16.8 15.4 14.6 1.5 5.2 11.6 10.2 9.4
Deshaun Watson 12.1 12.1 9.5 14.6 2.6 20.1 8 10.6 5.5
DeShone Kizer 12.2 12.2 8 14.6 4.1 22.1 9.9 14.1 7.5
Drew Brees 18.9 16.2 18.9 16.4 14.6 2.5 20.8 1.9 4.4 6.2
Eli Manning 16.1 14.4 16.1 11.8 14.6 4.3 22.6 6.5 10.8 8
Jacoby Brissett 10.9 16.9 10.9 9.2 14.6 1.7 27.8 16.9 18.6 13.2
Jameis Winston 13.5
Jared Goff 12.8 14.2 12.8 12.4 14.6 0.4 23.6 10.8 11.2 9
Jay Cutler 14.2 16.7 14.2 14.1 14.6 0 11.7 2.5 2.4 2.9
Joe Flacco 17.5 14.5 17.5 10.9 14.6 6.6 -2.9 20.4 13.8 17.5
Josh McCown 14.9 14.9 14.9 7.5 14.6 7.3 14.7 0.2 7.2 0.1
Kirk Cousins 18.3 18.4 18.3 14.7 14.6 3.6 26.8 8.5 12.1 12.2
Marcus Mariota 16 17.8 16 13.8 14.6 2.2 19.7 3.7 5.9 5.1
Matt Ryan 17.7 19.4 17.7 17 14.6 0.7 13.7 4 3.3 0.9
Matthew Stafford 17.6 17.6 17.6 15.5 14.6 2.1 16.5 1.1 1 1.9
Mike Glennon 7.8 16 7.8 9.3 14.6 -1.5 6.4 1.4 2.9 8.2
Philip Rivers 16.4 16.3 16.4 14 14.6 2.4 3.5 12.9 10.5 11.1
Russell Wilson 19.8 19.9 19.8 14.9 14.6 4.9 33.5 13.7 18.6 18.9
Tom Brady 17.9 16.1 17.9 19.7 14.6 -1.8 35.7 17.8 16 21.1
Trevor Siemian 15.5 15.1 15.5 13.9 14.6 1.6 7.6 7.9 6.3 7
Tyrod Taylor 17.7 19.4 17.7 12.8 14.6 4.9 17.8 0.1 5 3.2
Average 16.4 16.5 16.1 13.2 14.6 2.7 17.5 6.9 8.3 7.4
Strd Dev. 5.7 5.6 7.3

While over the first two weeks, my higher than average projections caused the results to be off, they proved themselves this week. The actual weekly average of 17.5 points was this season's highest weekly total. Overall, my projections were off by an average 6.9 points while the standard RotoWire projections were at 8.3 points off. The spread (standard deviation) was similar between the two systems.

Most of my misses (Brady, Flacco, Brissett, Wilson, Rivers) were also missed by the standard projections. Where my system did better was nailing some guys who the standard system was undervalued like Tyrod Tayler (0.1 points vs. 5.0 points off), Josh McCown (0.2 points vs. 7.2 points off) and Carson Palmer (0.7 points vs. 5.3 points). Who knows how far off the numbers will be next week, but I will take one good week. It may be my last.

Even though my projections work, I think I can keep improving them. While I planned to add defensive values to the equation this week, I made an improvement to quarterbacks instead, in-season target inclusion. While previous season data is useful, the addition of in-season data is a major improvement.

Using data from 1990 to 2016, I found out how much to weight previous and in-season pass attempts to predict the next game's rate. Here's a graph of the results

While preseason information never becomes irrelevant, it is only half of the estimate around Weeks 3 and 4. This three-week span likely applies to in-season data production as well. If a quarterback throws a ton of passes over a couple of weeks, it's important to notice the change and give him a 50/50 mix of old and new data. Don't go all in on historic or recent data. It will be a mix of both. If the trend continues, it can be believed more and more.

By week 10, 80 percent of the pass attempts should be in-season data. The in-season data doesn't completely take over but it's close by season's end.

By adding in the in-season pass attempts, I've created Week 4's quarterback projections.

PLAYERPROJ PAVEGAS POINTSPA POINTSHYBRIDROTOWIREDIFF
Aaron Rodgers 41.3 18.7 22.3 22.3 21.6 0.7
Russell Wilson 35.6 19.9 20.9 20.9 20.0 0.9
Drew Brees 40.0 16.2 18.9 18.9 21.2 -2.3
Carson Palmer 41.6 15.5 18.4 18.4 17.3 1.1
Tom Brady 37.6 16.1 18.1 18.1 23.1 -5.0
Matthew Stafford 36.4 17.6 17.7 17.7 15.7 2.1
Kirk Cousins 35.6 18.4 17.7 17.7 16.6 1.1
Matt Ryan 32.3 19.4 17.2 17.2 20.7 -3.5
Cam Newton 31.3 19.2 17.2 17.2 15.7 1.5
Ben Roethlisberger 36.0 16.1 17.0 17.0 15.8 1.2
Philip Rivers 36.6 16.3 17.0 17.0 17.4 -0.4
Carson Wentz 38.3 15.0 17.0 17.0 16.9 0.1
Andy Dalton 33.4 16.7 16.8 16.8 15.8 1.0
Dak Prescott 31.9 18.4 16.8 16.8 18.3 -1.5
Eli Manning 38.3 14.4 16.7 16.7 15.0 1.8
Tyrod Taylor 28.0 19.4 16.4 16.4 16.9 -0.5
Marcus Mariota 31.4 17.8 16.3 16.3 17.5 -1.2
Jameis Winston 35.4 10.8 16.2 16.2 16.9 -0.7
Alex Smith 30.7 18.7 16.1 16.1 16.8 -0.7
Blake Bortles 34.8 15.1 16.1 16.1 15.5 0.5
Derek Carr 34.4 17.4 15.9 15.9 15.9 -0.0
Case Keenum 33.4 10.9 15.4 15.4 12.4 3.0
Trevor Siemian 34.1 15.1 15.4 15.4 16.8 -1.4
Brian Hoyer 33.2 15.1 15.0 15.0 10.6 4.4
Joe Flacco 34.1 14.5 14.9 14.9 13.0 1.9
Josh McCown 31.2 14.9 14.0 14.0 9.7 4.3
Jay Cutler 26.7 16.7 13.1 13.1 15.8 -2.7
Deshaun Watson 32.1 12.2 12.2 13.3 -1.1
DeShone Kizer 32.0 12.1 12.1 10.7 1.5
Jacoby Brissett 24.0 16.9 12.0 12.0 9.1 2.9
Jared Goff 28.3 14.2 12.0 12.0 16.9 -4.9
Mike Glennon 21.3 16.0 10.3 10.3 11.2 -0.9
Average 33.5 16.1 16.3 16.0 15.9 0.1

The two projection results have melded to similar values. Only four players are off by more than four points. I'm higher on McCown and Hoyer and lower on Brady and Goff. Additionally, the average values are only 0.1 off, so the two projection systems are closer after being separated by ~3 points last week.

Wide Receivers

Last week may have been the first and last week for wide receiver projections this year. The basic issue is that I don't have access to an in-season database to link my rate projections and target estimates. I already match the quarterback information by hand, but they are limited to about 30 players who rarely change. With wide receivers, I would need to match up data on 100-plus players. I just don't have the time.

I went back and looked at the top wide receivers from last week and which projection system did best on these few guys. It wasn't mine.

PLAYERACTUALROTOWIREDIFFZMAN'SDIFF
Stefon Diggs 29.3 8.1 21.2 7.4 21.9
Brandin Cooks 27.1 11.0 16.2 7.7 19.4
Sammy Watkins 22.6 8.6 14.0 4.8 17.8
T.Y. Hilton 21.3 8.3 13.0 9.5 11.8
Larry Fitzgerald 20.9 8.2 12.7 8.3 12.6
Sterling Shepard 19.3 7.0 12.3 6.4 12.9
Chris Hogan 18.8 7.7 11.1 4.9 13.9
Jordy Nelson 17.2 11.9 5.3 6.6 10.6
A.J. Green 17.1 13.3 3.8 10.5 6.6
Antonio Brown 17.0 15.3 1.7 11.1 5.9
Doug Baldwin 16.5 10.6 5.9 8.5 8.0
Robby Anderson 15.5 4.7 10.8 4.8 10.7
Brice Butler 15.0 2.5 12.5 2.3 12.7
Tyreek Hill 15.0 10.9 4.1 8.1 6.9
Rishard Matthews 14.7 8.3 6.4 6.4 8.3
Michael Thomas 14.7 10.9 3.8 11.5 3.2
DeSean Jackson 14.4 8.3 6.1 6.0 8.4
Pierre Garcon 14.2 8.5 5.7 6.7 7.5
Taylor Gabriel 13.9 7.2 6.7 5.0 8.9
DeVante Parker 13.6 10.0 3.7 8.1 5.5
Geronimo Allison 12.2 8.5 3.7 4.6 7.6
Ted Ginn 11.9 8.1 3.8 4.4 7.5
Golden Tate 11.8 10.3 1.5 5.4 6.4
Average 17.1 9.0 8.1 6.9 10.2

My projections on this player set were lower, so when they overperformed, I was way off with the top guys. The issue is that I don't know the results for all the players. Hopefully, I can at a future date.

One piece of information I extracted before moving on was how much to weigh preseason and in-season targets. Here's the information.

The resulting weights are like the quarterback numbers with the in-season data taking precedence around week three. Additionally, the in-season becomes 100 percent of the projection in week 15. In the last couple weeks, all preseason can be thrown out.

I think that I'm able to continue to make progress but for now, I won't be able to advance future with wide receivers until I fix my database issue. Incorporating some opposing defensive values is still a major step for the quarterbacks. I hope to do them for next week. Until them, good luck setting your lineups.

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ABOUT THE AUTHOR
Jeff Zimmerman
Jeff is a former RotoWire contributor. He wrote analytics-focused baseball and football articles for RotoWire. He is a three-time FSWA award winner, including the Football Writer of the Year and Best Football Print Article awards in 2016. The 2017 Tout Wars Mixed Auction champion and 2016 Tout Wars Head-to-Head champ, Zimmerman also contributes to FanGraphs.com, BaseballHQ and Baseball America.
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